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Hands-On Recommendation Systems with Python

You're reading from   Hands-On Recommendation Systems with Python Start building powerful and personalized, recommendation engines with Python

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Product type Paperback
Published in Jul 2018
Publisher Packt
ISBN-13 9781788993753
Length 146 pages
Edition 1st Edition
Languages
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Author (1):
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Rounak Banik Rounak Banik
Author Profile Icon Rounak Banik
Rounak Banik
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Toc

Hybrid Recommenders

In this final chapter, we will discuss recommender systems in the context of practicality and industrial use. Until now, we have learned about various types of recommender, including knowledge, content, and collaborative filtering-based engines. However, when used in practice, each recommender usually suffers from one shortcoming or another.

We've discussed these shortcomings in the very first chapter (for instance, the novelty problem of content-based engines and the cold start problem of collaborative filters). We also briefly introduced the concept of the hybrid recommender: a robust system that combines various models to combat the disadvantage of one model with the advantage of another. In this chapter, we will build a simple hybrid recommender that combines the content and the collaborative filters that we've built thus far.

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